Welcome to my monthly newsletter. I'm an experienced software engineer, a tech mentor to product managers, and the founder of Skiplevel. Every month I share:
- technical skills and knowledge you should know
- tips for working with and collaborating with dev teams
- tips for non-engineers struggling with confidence in technology
- tips for managers looking to build a more technically literate team
Ask me anything (yep, anything) and I'll cover it in an upcoming newsletter issue!
Q: ChatGPT is blowing up right now and there’s a lot of social posts and articles floating around on how to use it for product management, but wondering if you had ideas for how to use it for working with devs specifically or becoming more technical?
Asked by Product Owner @ Spring.io
Hey PO @ Spring,
It seems like come every season there’s some new tech we need to take advantage of lest we miss out (FOMO anyone?). This time last year it was Web3, before that it was the metaverse, then it was crypto, NFTs, and now it’s generative AI and ChatGPT.
But unlike the previous buzz-techs, ChatGPT has real stickiness for a wide range of use cases and professions, including product management.
So your question is right on the money. I played around a bunch with ChatGPT and came up with 3 use cases for supplementing your technical literacy journey and working with your engineering team:
- Understanding spoken and written tech jargon
- Write SQL queries
- Get a list of possible technical solutions to explore with dev team
Use case #1: Understanding spoken and written tech jargon
Let’s say you’re in the middle of a meeting with engineers. They’re discussing technical solutions to a problem. Tech jargon is being thrown around willy nilly and before you know it, you’re lost and totally checked out.
What’s worse, you want to ask a question but you’re too afraid to for fear of looking stupid.
This is a great scenario for using ChatGPT. During discussions like this, you can ask ChatGPT to explain what a tech term means.
Here’s a useful tip: ask ChatGPT to answer the question in simple terms.
Tangentially, you can also ask ChatGPT to explain written technical Jargon.
For example, imagine your team is using Hadoop so you decide to learn more about it. You hop onto Hadoop’s webpage and you get to this line:
“Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.”
… That’s a lot of tech jargon and context in this one sentence.. What does high-availability mean? What does it mean to handle failures at the “application level”?.. and what in the world is a cluster?
If we ask ChatGPT to explain what it means in simple terms, it’ll define the technical jargon and then summarize the sentence as a whole. If you’re still confused, you can ask it to clarify further the way you would if it was an actual engineer. Neat right?
Use Case #2: Use ChatGPT to write and learn SQL
Writing SQL as a product manager/non-engineer can be tricky, but SQL is a valuable skill for product managers for two main reasons:
- You’re not dependent on engineers to provide you the data you need, which also means not having to wait around.
- It’s a plus for engineers since it takes work off their plates to focus on more feature-rich tasks.
This is where ChatGPT comes in. ChatGPT is able to write and dissect code, which means you can ask it to write SQL queries for you. So I decided to roll up my sleeves and try it out myself.
Got a question? Ask me anything & I'll cover it in an upcoming issue!
This month's Tech Term you should know:
Webhooks is a communication design pattern and it's a popular way for apps to provide real-time information to other apps via sending automated messages. They're automated messages sent from apps when something happens (a trigger event).
In the webhooks design, there are 3 main parts:
- Webhook origin: App where trigger event happens
- Webhook recipient: App that processes data sent from the webhook origin
- Webhook URL: The URL or address (lives within the webhook recipient) that the webhook origin sends message to when trigger event happens
Here's a real-world example:
Let's say you set up a webhook on your Slack channel to get a message whenever a new task is added to your Jira sprint board (or whichever project management tool you use).
A team member creates a new task on the team's Jira board (trigger event) → the Jira app (webhook origin) sends a message to Slack's webhook URL (webhook recipient) → the Slack app posts a message to your Slack channel with the data it received from the Jira app.
How webhooks are used in the real-world
There are 2 important things to note about webhooks:
- First, the webhook origin sends messages to the webhook recipient automatically when the trigger event happens. The automation is what makes webhooks so powerful and so widely used.
- Second, webhooks are uni-directional communication. This means the webhook origin app can send a message to the webhook recipient, but the webhook recipient won't initiate connection and message sending to the webhook origin. This point is important to differentiate between webhooks and websockets.
Webhooks is the technology you're leveraging when using workflow automation tools like Zapier. Workflow automation tools like Zapier has webhook URLs from thousands of apps and allow you to plug-and-play any of these webhooks together to create automatic and seamless workflows.
Hot Twitter Takes 👀
Apply this for everything. While writing requirements -> Can I show this in a diagram/mock?; While trying to communicate complex if/else flows -> Let me use a if/else flow diagram; While writing documents -> Only use facts and figures when necessary, otherwise focus on narrative!
The LinkedIn- and Twitter-verse is awesome :) Wanna learn SQL? Check out the resources below:
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